Portugal Covid-19 Analysis

db <- db <- dbConnect(RSQLite::SQLite(),dbname= "../COVID-19-DB/OURWORLD.sqlite3")
portugal <- dbGetQuery(db,"select * from OWID where location ='Portugal'")
portugal$date <- as.Date(portugal$date)
## Clean Data

portugal <- janitor::clean_names(portugal)
portugal <- janitor::remove_empty(portugal,which = c("cols","rows"))
portugal$date <- as.Date(portugal$date)
dim(portugal)

## [1] 625  60

Portugal : Analysis of Cases, Deaths and Vaccination Rate

# Calculate Vaccination Rate i.e Poeple Vaccinate / Population

portugal<- portugal %>% mutate(vacc_rate = people_vaccinated/population)

# Calculate 14 day moivng average
portugal$avg_cases <-  ma(portugal$new_cases,14,centre = TRUE)


portugal$avg_deaths <- ma(portugal$new_deaths,14,centre = TRUE)

Plot of Daily Cases and Daths w/ 14 Day Moving Avearge

p1 <- portugal  %>% ggplot() +
  geom_line(aes(x=date,y=new_cases,col="Daily Cases"),lwd=1) +
   geom_line(aes(x=date,y=avg_cases,col="Moving Avg."),lwd=1) +
  labs(title = "Daily cases + 14 Day Moving Average",y="Daily Cases",x="Date")
ggplotly(p1)

p2 <- portugal %>% ggplot() +
  geom_line(aes(x=date,y=new_deaths,col="Daily Deaths"),lwd=1) +
   geom_line(aes(x=date,y=avg_deaths,col="Moving Avg."),lwd=1) +
  labs(title = "Daily Deaths + 14 Day Moving Average",y="Daily Deaths",x="Date")
ggplotly(p2)

Cases and Deaths by Week

p3 <- portugal %>% summarize_by_time(.by ="week",value=sum(new_cases)) %>% na.omit() %>% ggplot(aes(x=date,y=value)) + geom_col() +
  labs(title = "Weekly Cases")

## .date_var is missing. Using: date

ggplotly(p3)

p4 <- portugal %>% summarize_by_time(.by ="week",value=sum(new_deaths)) %>% na.omit() %>% ggplot(aes(x=date,y=value)) + geom_col() +
  labs(title = "Weekly Deaths")

## .date_var is missing. Using: date

ggplotly(p4)

Cases and Deaths by Month

p5 <- portugal %>% summarize_by_time(.by ="month",value=sum(new_cases)) %>% na.omit() %>% ggplot(aes(x=date,y=value)) + geom_col() +
  labs(title = "Monthly Cases")

## .date_var is missing. Using: date

ggplotly(p5)

portugal %>% summarize_by_time(.by ="month",value=sum(new_deaths)) %>% na.omit() %>% ggplot(aes(x=date,y=value)) + geom_col() +
  labs(title = "Monthly Deaths")

## .date_var is missing. Using: date